EDA

Some 1/2 hour segments have NAs for all values (how did he handle them?) Also some don’t have all NAs - which is interesting… Finally, some of the final rows are all NAs.

tc_rad %>% is.na %>% apply(1, sum) %>% head(100)
##   [1]   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##  [19]   0   0   0  75  76  77  78   0   0   0   0   0   0   0   0   0   0   0
##  [37]   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##  [55]   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##  [73] 120   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##  [91]   0   0   0   0   0   0   0   0   0   0
# interestingly some don't completely have all NAs...
some_na <- tc_rad %>% is.na %>% apply(1, sum) %>% sapply(function(v) v> 0)
na_grouping <- some_na %>% cumsum()
na_grouping %>% table # let's look at 9
## .
##  0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 
## 21  1  1  1 48 48 21 27 48 48 21 27 32  1  1  1  1  1  1  1  1  1  1  1  1  1 
## 26 27 28 29 30 
##  1  1  1  1  1

Visual:

This visual is a the 9th segment (relative to NAs) - and is not the overall full time span of the hurricane.

Visual 2

Rapid intensity time (August 26-28)